This function will generate n random points from a zero truncated
Geometric distribution with a user provided, .prob, and number of
random simulations to be produced. The function returns a tibble with the
simulation number column the x column which corresponds to the n randomly
generated points, the d_, p_ and q_ data points as well.
The data is returned un-grouped.
The columns that are output are:
sim_number The current simulation number.
x The current value of n for the current simulation.
y The randomly generated data point.
dx The x value from the stats::density() function.
dy The y value from the stats::density() function.
p The values from the resulting p_ function of the distribution family.
q The values from the resulting q_ function of the distribution family.
tidy_zero_truncated_geometric(
.n = 50,
.prob = 1,
.num_sims = 1,
.return_tibble = TRUE
)A tibble of randomly generated data.
The number of randomly generated points you want.
A probability of success in each trial 0 < prob <= 1.
The number of randomly generated simulations you want.
A logical value indicating whether to return the result as a tibble. Default is TRUE.
Steven P. Sanderson II, MPH
This function uses the underlying actuar::rztgeom(), and its underlying
p, d, and q functions. For more information please see actuar::rztgeom()
https://openacttexts.github.io/Loss-Data-Analytics/ChapSummaryDistributions.html
Other Geometric:
tidy_geometric(),
util_geometric_param_estimate(),
util_geometric_stats_tbl()
Other Continuous Distribution:
tidy_beta(),
tidy_burr(),
tidy_cauchy(),
tidy_chisquare(),
tidy_exponential(),
tidy_f(),
tidy_gamma(),
tidy_generalized_beta(),
tidy_generalized_pareto(),
tidy_geometric(),
tidy_inverse_burr(),
tidy_inverse_exponential(),
tidy_inverse_gamma(),
tidy_inverse_normal(),
tidy_inverse_pareto(),
tidy_inverse_weibull(),
tidy_logistic(),
tidy_lognormal(),
tidy_normal(),
tidy_paralogistic(),
tidy_pareto(),
tidy_pareto1(),
tidy_t(),
tidy_triangular(),
tidy_uniform(),
tidy_weibull()
Other Zero Truncated Distribution:
tidy_zero_truncated_binomial(),
tidy_zero_truncated_poisson(),
util_zero_truncated_binomial_param_estimate()
tidy_zero_truncated_geometric()
Run the code above in your browser using DataLab